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Machine learning

Applications

• Image classification | Object detection | Object recognition | Semantic segmentation
• Face detection | Pedestrian detection
• Speech recognition | Sentiment analysis | Machine translation

Networks

• Networks: CNN | RNN | GAN | Deconvnet | AutoEncoder

Common terms

• Training | Inference
• Model : Parameter | Layer | Accuracy
• Neural network : Neuron | Perceptron | Weight | Bias | Activation function | Depth
• Dataset : Feature | Label
• Data formats : FP16 | FP32 | bfloat16 | INT8

Training terms

• Learning types: Supervised | Unsupervised | Federated | Reinforcement
• Supervised Learning : Classification | Regression
• Unsupervised Learning : Clustering
• Example : Labeled example | Unlabeled example
• Loss : Loss function
• Passes : Backpropagation | Forward pass | Backward pass
• Gradient Descent algorithm: SGD | Batch | Mini-batch
• Batch : Mini-Batch | Batch Size | Iteration
• Hyperparameter : Learning rate | Epoch
• Overfitting | Underfitting
• Regularization : Dropout
• Quantization

State-of-the-art and benchmarks

• Image classification: AlexNet | VGG | ResNet | Inception | EfficientNet | Vision Transformer
• Object detection: R-CNN | Fast R-CNN | Faster R-CNN | Mask R-CNN | Yolo
• NLP: BERT
• MLPerf : MLPerf Inference | MLPerf Training | MLCommons
• Data sets : MNIST | ImageNet | COCO | PASCAL VOC | CIFAR

ML Software

• Frameworks: TensorFlow | PyTorch | vLLM | SGLang | ONNX | JAX
• Inference engines: OpenVINO | TensorRT | TensorFlow Lite | Core ML
• Libraries: cuDNN | MKL-DNN | Arm Compute Library | XNNPACK | QNNPACK
• BLAS libraries: Eigen | OpenBLAS | MKL | BLIS | cuBLAS
• Compiler tech: MLIR | TensorFlow XLA | TVM

TensorFlow related

• TensorFlow | TensorFlow.js | TensorFlow Lite | TensorFlow Serving
• TensorFlow Versions
• TFRT | MLIR | TensorFlow XLA
• TensorBoard | TensorFlow Hub
• Eigen | MKL-DNN

Companies

• Google | Meta | Microsoft | Amazon
• Arm | AMD | Intel | Nvidia